Sentence Similarity
PEFT
Safetensors
English
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
text-reranking
feature-extraction
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results
Update README.md
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README.md
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@@ -66,7 +66,7 @@ model = model.merge_and_unload() # This can take several minutes on cpu
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# Loading unsupervised SimCSE model. This loads the trained LoRA weights on top of MNTP model. Hence the final weights are -- Base model + MNTP (LoRA) + SimCSE (LoRA).
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model = PeftModel.from_pretrained(
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model, "McGill-NLP/LLM2Vec-Mistral-7B-Instruct-v2-unsup-simcse"
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)
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# Wrapper for encoding and pooling operations
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# Loading unsupervised SimCSE model. This loads the trained LoRA weights on top of MNTP model. Hence the final weights are -- Base model + MNTP (LoRA) + SimCSE (LoRA).
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model = PeftModel.from_pretrained(
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model, "McGill-NLP/LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse"
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)
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# Wrapper for encoding and pooling operations
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